CN111095344A

CN111095344A - Sample type identification device, analysis system, and analysis network system

Info

Publication number: CN111095344A
Application number: CN201780094814.8A
Authority: CN
Inventors: 铃木桂次郎
Original assignee: Shimadzu Corp
Current assignee: Shimadzu Corp
Priority date: 2017-09-11
Filing date: 2017-09-11
Publication date: 2020-05-01
Anticipated expiration: 2037-09-11
Also published as: US20200201917A1; WO2019049354A1; JP6849082B2; EP3683693A1; CN111095344B; EP3683693A4; JPWO2019049354A1

Abstract

An apparatus for specifying a class to which a target sample belongs from among a plurality of classes, each of which is defined with a reference and which classifies the sample, the apparatus comprising: a storage unit (21) that stores a database (211) in which one or more words related to a criterion predetermined for each of a plurality of categories are associated with each of the categories (211); a target sample information input receiving unit (24) for receiving input of target sample information, the target sample information being language information including a word that characterizes a target sample; a category candidate extraction unit (26) that compares the term included in the target sample information with the one or more terms corresponding to each of the plurality of categories, and extracts a candidate for the category to which the target sample belongs from the plurality of categories on the basis of the degree of matching between the terms; and a category candidate presentation unit (27) for presenting the candidates of the extracted category to the user.

Description

Sample type identification device, analysis system, and analysis network system

Technical Field

The invention relates to a device which comprises: in order to determine a reference for comparing measurement data of a target sample from among predetermined references for each of a plurality of classes for classifying samples, a class to which the target sample belongs is determined. The present invention also relates to an analysis system and an analysis network system provided with such an apparatus.

Background

In recent years, various standards have been set in each country and each region in order to prevent products containing harmful substances from being imported into the country (or region) and distributed. One of such references is a reference called RoHS (Restriction of Hazardous Substances) directive, which is defined by the European Union (EU). In the RoHS directive, the use of six harmful substances, namely lead, mercury, cadmium, hexavalent chromium, PBB (polybrominated biphenyls) and PBDE (polybrominated diphenyl ethers), is prohibited in principle for various electrical and electronic devices, and exclusion regulations are stipulated in the case where there is no alternative to the use of these harmful substances. The allowable content of the harmful substance is defined in the rule of exclusion. Manufacturers of electrical and electronic equipment that are exported to the european union are obligated to prove that the equipment meets the requirements of the RoHS directive. Therefore, when manufacturing such an electric and electronic device, an analyst uses an analysis apparatus such as a fluorescent X-ray analysis apparatus to quantify the amount of the harmful substance contained in each material, and if the harmful substance is contained, checks whether or not the harmful substance meets the exclusion rule specified in the category to which the device belongs (for example, patent document 1).

Conventionally, when an analyst performs the above-described operation, the harmful substances contained in the respective materials are sequentially measured and quantified, and the results are stored together with the names of the materials and the like. After the measurement of all the materials is completed, the quantitative values of the harmful substances are sequentially called up and compared with the allowable amounts described in the regulation of elimination of the RoHS directive, to determine whether the materials are acceptable or not.

Documents of the prior art

Patent document

Patent document 1: japanese patent laid-open publication No. 2013-217915

Non-patent document 1: "japanese -form element resolution (japanese morpheme resolution)", [ online ], metro-bb.com, [ search 4/14/2017 ], internet < URL: http: [ batches.metro-bb.com/api/keitasso >

Non-patent document 2: "extraction of the processing under テキストツールキーフレーズ" (extraction of keyword by text processing tool) ", [ online ], [ search at 4/14/2017 ], internet < URL: http: jp/web-app/text/key-phrase/>/so-zou

Disclosure of Invention

Problems to be solved by the invention

In the RoHS directive, electric and electronic devices are classified into fine categories, and the details excluding the regulations, that is, the types of harmful substances and the allowable contents for the harmful substances, vary for each category. Therefore, the analyst must find out the category to which the electric and electronic device using the material belongs for each material, check the exclusion rule described in association with the category, and determine whether the material is acceptable or not, which is a great burden for the analyst.

Although the RoHS directive has been described as an example, various standards such as ELV (End of Life Vehicles) directive, REACH (Registration, Evaluation, Authorization, and Restriction of Chemicals) are defined for use of hazardous substances, and the like, and the same problems as described above are also present when the standards are compared with each other. In addition, the same problem as described above is caused not only in the determination of the content of the harmful substance contained in the material, but also in the work of determining the standard corresponding to a product from among a plurality of standards defined for each product category when measurement data obtained by sampling and analyzing a part of the product is compared with a predetermined standard in order to confirm that the product manufactured in a factory or the like is a non-defective product satisfying the predetermined standard.

In the following description, not only the category in which the sample (material or the like) itself is defined is referred to as "category for classifying the sample", but also the category in which a product or the like using the sample (material or the like) is defined (that is, the category in which the sample is indirectly defined) as in the RoHS directive is referred to as "category for classifying the sample".

The problem to be solved by the present invention is to provide a sample type identification device: the load on an analyst in identifying a class to which a target sample belongs from among a plurality of classes for classifying samples, each of which has a predetermined reference, can be reduced.

Means for solving the problems

A sample type determination device according to the present invention, which has been achieved to solve the above problems, is a sample type determination device for determining a type to which a target sample belongs from among a plurality of types, each of which is defined with a reference, and which classifies samples, the sample type determination device including:

a) a storage unit that stores a database in which one or more words related to a criterion predetermined for each of a plurality of categories are associated with each of the categories;

b) a target sample information input receiving unit for receiving input of target sample information, the target sample information being language information including a word that characterizes a target sample;

c) a category candidate extraction unit that compares the word included in the target sample information with the one or more words corresponding to each of the plurality of categories, and extracts a candidate of a category to which the target sample belongs from the plurality of categories according to a degree of coincidence therebetween; and

d) a category candidate presentation unit for presenting candidates of the extracted category to the user.

The target sample information may be a single word or a set of multiple words, or may be a sentence composed of multiple words by a grammatical relationship. Here, the term "word" includes a numerical value, a chemical formula of a substance, and the like, in addition to a normal word classified into a noun, a verb, and the like, which are components of a normal language. The category candidate extraction unit may extract a category candidate to which the target sample belongs from the plurality of categories by obtaining the matching degree by comparing the word with a plurality of words corresponding to each of the plurality of categories when the word is input, and may extract the category candidate to which the target sample belongs from the plurality of categories by obtaining how many of the plurality of words are included in the sentence when the sentence is input.

In the sample type determination device according to the present invention, the type to which the target sample belongs is determined using a database in which one or more words related to a reference predetermined for each of a plurality of types are associated for each of the types. When the user inputs language information (target sample information) including a word that characterizes a target sample, the category candidate extraction unit obtains the degree of matching between the word included in the target sample information and one or more words associated with each category, and extracts a category candidate to which the target sample belongs, as described above. Then, the category candidate presenting section presents the candidate to the user. In this apparatus, candidates of a category to which a target sample belongs can be presented only by the user inputting sample information, and therefore, the burden on the user (analyst) is reduced.

The sample type identification device according to the present invention may be configured to further include:

e) a reference information input receiving unit for receiving input of reference information, which is language information in which a reference predetermined for one category is described;

f) a morphological analysis unit that extracts one or more words from the reference information by performing morphological analysis on the reference information; and

g) and a database storage unit that stores the extracted one or more words in the database in association with the one category.

The reference information may be a word or a set of words, or may be a sentence composed of these words by a prescribed syntax. When a word or a set of words is input, the morpheme analyzing unit stores the words in the database as they are, and when a sentence is input, the morpheme analyzing unit performs morpheme analysis on the sentence, extracts a plurality of words, and stores the words in the database.

A sentence in which a standard predetermined for one category is described means, for example, a "general lighting application is less than 30W/bulb type and compact (compact) type fluorescent lamp and the mercury content is not more than 5mg per base" described in RoHS directive. In the apparatus of the above-described embodiment, morpheme analysis is performed on the words to extract a plurality of words. In this example, words such as "normal", "illumination", "use", "30", "deficiency", "bulb" and the like are generated by morpheme analysis. The generated plurality of words is then saved to a database in association with the category. For morpheme analysis, software such as "chasan" and "MeCab" or the same algorithm as the software can be used.

In the sample type determination device according to the above-described aspect, the database can be automatically created simply by sequentially inputting the reference sentences for each type. In addition, newly established criteria can be sequentially and easily added to the database.

In the above-described sample type determination device, it is preferable that,

the morpheme analyzing unit extracts only nouns and verbs from the reference information.

In general, when a sentence is subjected to morpheme analysis, words of various parts of speech such as nouns, verbs, auxiliary verbs, and adverbs are generated. However, the verb assistants, adverbs, and the like hardly contribute to locking of candidates of the category to which the sample belongs. As described above, by adopting the configuration in which the morpheme analyzing unit extracts only nouns and verbs to create word groups, the number of words stored in the database can be reduced, and the processing for comparing the sample information with the word groups of each category by the category candidate extracting unit can be speeded up. In addition, the term as used herein includes numerical values, chemical formulas of substances, and the like.

In the sample type determination device according to the present invention, it is preferable that the morpheme analyzing unit extracts a keyword from the reference information.

As software for extracting a keyword group from a sentence, software described in, for example, non-patent document 1 and non-patent document 2 is known in the past. When a sentence "lead is contained as an alloy component in a steel material and up to 0.35 wt% in a galvanized steel sheet for machining" is input to these software, a keyword of "in a galvanized steel sheet", "in an alloy component", "in a machining", "in a steel material", and "0.35 wt%" is extracted as a keyword in any software. By using such a keyword group, candidates of a category to which the sample belongs can be extracted with higher accuracy.

The sample type identification device according to the present invention may have the following configuration:

the morpheme analyzing unit extracts a word composed of a combination of a numerical value included in the keyword group, a unit of a physical quantity, and a predetermined word indicating a magnitude relationship with the numerical value, and creates a numerical expression based on the extracted word,

the database creating unit creates a database by associating the numerical expression with the one category.

The predetermined words indicating the magnitude relationship between the above-mentioned terms and numerical values are, for example, "insufficient", "below", "small", "few", "not more than", "up to", "same", "equal", "more than", "larger", and the like. When such a keyword is included, the keyword is digitized and compared with the input keyword. For example, when there is a keyword group of "general lighting application is less than 30W", the keyword group is digitized as "X < 30W" (X is an input value of a user) to create a database.

In many cases, the word comprised of a combination of a numerical value and a unit of a physical quantity included in the reference sentence describing each category is a value for determining the category to which the target sample belongs, and a value for use as a criterion for determining whether the target sample is acceptable or not in the category. By using the sample type identification device of the above-described embodiment including the numerical value extraction unit, the user can clearly confirm the type to which the target sample belongs and the reference value that is the reference for determining whether the sample is acceptable or not, and the burden on the user (analyst) can be further reduced.

ADVANTAGEOUS EFFECTS OF INVENTION

By using the sample type identification device according to the present invention, it is possible to reduce the burden on the analyst when identifying the type to which the target sample belongs from among a plurality of types for classifying samples, each of which has a predetermined reference.

Drawings

Fig. 1 is a main part configuration diagram of an embodiment of a sample type determination device according to the present invention.

Fig. 2 is a diagram illustrating a sample type database according to an embodiment.

Fig. 3 is an example of an initial screen of the sample type specifying device according to the embodiment.

Fig. 4 is an example of an input screen of target sample information of the sample type specifying device according to the embodiment.

Fig. 5 is an example of a display screen of the type candidates of the sample type specifying device according to the embodiment.

Fig. 6 is an example of a determination criterion input screen of the sample type specifying device according to the embodiment.

Fig. 7 is a main part configuration diagram of an embodiment of an analysis system according to the present invention.

Fig. 8 is an example of a threshold value used in screening analysis by the energy dispersive fluorescent X-ray analysis apparatus.

Fig. 9 is an example of an initial screen of the analysis system of the embodiment.

Fig. 10 is an example of a display screen of category candidates of the analysis system of the embodiment.

Fig. 11 is an example of a display screen of the determination result of the analysis system of the embodiment.

Fig. 12 is a main part configuration diagram of an embodiment of an analysis network system according to the present invention.

Detailed Description

Hereinafter, embodiments related to the sample type identification device, the analysis system, and the analysis network system according to the present invention will be described.

The sample type determination device of the present embodiment is used to determine to which of the categories specified in the exclusion regulation regarding six harmful substances, i.e., lead, mercury, cadmium, hexavalent chromium, PBB (polybrominated biphenyls), PBDE (polybrominated diphenyl ethers), in the RoHS directive the target sample belongs. The rule for eliminating the RoHS directive describes the category into which the electric and electronic devices are classified, and the material (sample) used in manufacturing the electric and electronic devices is indirectly classified into any one of these categories according to the type of the electric and electronic devices. Hereinafter, the category for indirectly classifying the sample is also referred to as "category for classifying the sample" as appropriate.

As shown in fig. 1, the sample type determination device according to the present embodiment includes a data processing unit 20, and an input unit 40 and a display unit 50 connected to the data processing unit 20. The data processing unit 20 includes, as functional blocks, a reference information input receiving unit 22, a morpheme analyzing unit 23, a target sample information input receiving unit 24, a database storage unit 25, a category candidate extracting unit 26, a category candidate presenting unit 27, and a language designation receiving unit 28 in addition to the storage unit 21. The data processing unit 20 is a personal computer, and executes a sample type identification program installed in the computer to implement these functional blocks.

The storage unit 21 stores a sample type database 211. As shown in fig. 2, the sample category database 211 is a table in which a sentence with a predetermined exclusion, in which a plurality of categories for classifying materials correspond to the predetermined exclusion of the RoHS rule, are associated with each other, and a keyword group extracted from the sentence. The numerical expressions included in the key phrases are also described later.

Next, the operation of the sample type specifying device according to the present embodiment will be described.

When the user makes the data processing program run, an initial screen as shown in fig. 3 is displayed. Three buttons of "sample type confirmation", "determination criterion input", and "language change" are displayed on the initial screen. The operation when these buttons are pressed will be described in order.

When the user presses the "sample type confirmation" button on the initial screen in fig. 3, the target sample information input receiving unit 24 displays a field (fig. 4) for allowing the user to input target sample information, which is language information including a word for giving a feature to a target sample, on the screen.

When the user inputs three keywords, for example, "fluorescent lamp", "40W", and "illumination use", as target specimen information and presses the "match" button, the category candidate extraction unit 26 matches the three keywords with the keyword group of the specimen category database 211, and extracts the number of matches. In addition, the term "match" as used herein includes not only complete match but also partial match. When a keyword including a numerical value (40) and a unit (W) of a physical quantity, such as "40W", is input as in the present embodiment, the keyword is not only directly collated with a keyword group, but also collated with a numerical expression included in the keyword group. In this embodiment, the keyword "40W" input by the user is compared with the numerical expression "< 30W" included in the keyword group, and the match/mismatch is determined according to the appropriateness of the keyword.

The category candidate extraction unit 26 compares the keyword input by the user with the keyword groups (including the numerical expressions) of all categories, and extracts a predetermined number of categories in descending order of their degree of matching. The extracted category is displayed on the display unit 50 by the category candidate presentation unit 27 as a candidate for a category to which a sample having a feature given by a keyword input by the user belongs. Fig. 5 shows an example of display. In fig. 5, both the matching number and the matching rate of the keyword are shown as the matching degree, but only one of them may be used as the matching degree. In addition, when the length of the sentence excluding the predetermined (criterion) is greatly different depending on the category, there are cases where: even if the number of matches between the keyword and the keyword group input by the user is large, the matching rate of the category is relatively low because the number of keyword groups of the category is large. Therefore, in this case, it is preferable to extract a predetermined number of categories based on the matching number. In the example of fig. 5, the number of categories to be extracted is set to three, but the user can change the number as appropriate.

When the user inputs language information (target sample information) including a plurality of words characterizing a target sample, such as "40W fluorescent lamp for general illumination", and presses the "morpheme analysis" button, the morpheme analysis unit 23 generates a plurality of words from the words. Then, the category candidate extraction unit 26 compares the plurality of words generated by the morpheme analysis unit 23 with the keyword sets in the sample category database 211. Then, a prescribed number of categories are extracted in order of their degree of coincidence from high to low.

When the user presses the "criterion input" button on the initial screen image in fig. 3, the criterion information input reception unit 22 displays language information for allowing the user to input a criterion (such as a criterion for eliminating the RoHS command) as a screen image of the criterion information on the display unit 50 ((a) in fig. 6). In addition, a button for causing the user to select one of the two processes of "keyword group extraction" and "morpheme parsing" is displayed. When the user presses "keyword extraction", the morpheme analyzing unit 23 extracts a keyword from the reference information (fig. 6 (b)). As software for extracting a keyword group from a sentence, for example, software described in non-patent document 1 or non-patent document 2 can be used.

Next, the morpheme analyzing unit 23 checks whether or not a word composed of a combination of a numerical value, a unit of a physical quantity, and a predetermined word indicating a magnitude relation with the numerical value exists in the keyword group, and if so, creates a numerical expression based on the word. The term "predetermined word" includes, for example, "insufficient", "smaller", "not larger", "equal", "larger", and the like. When such a keyword is included, the keyword is digitized and compared with the input keyword. For example, when there is a keyword such as "general illumination use is less than 30W", the keyword is digitized as "X < 30W" (X is an input value of a user) to create a database.

When the user presses "morpheme analysis", the morpheme analysis unit 23 performs morpheme analysis on the reference information and extracts a plurality of words ((c) of fig. 6.) the plurality of keyword groups and numerical expressions (or a plurality of words) obtained in this way are stored in the sample type database 211 by the database storage unit 25 together with the reference information before processing.

In the example of fig. 6 (c), morpheme analysis is performed to extract only nouns and verbs. When a sentence is morpheme-analyzed, words of various parts of speech such as nouns, verbs, auxiliary verbs, and adverbs are generated. However, the verb assist and adverb hardly contribute to the locking of candidates of the category to which the sample belongs. As in the present embodiment, by adopting the configuration in which the morpheme analyzing unit extracts only nouns and verbs to create word groups, the number of words stored in the database can be reduced, and the processing for comparing the sample information with the word groups of each category by the category candidate extracting unit can be speeded up. The term "chemical" as used herein includes numerical values, chemical formulas of substances, and the like. Of course, a part-of-speech selection column or the like may be displayed, and the user can appropriately change the part of speech extracted during the morpheme analysis.

The "language change" button in fig. 3 is a button for changing the language used in the present system from the language (e.g., japanese) set initially. When the user presses the button, the user is presented with multiple languages such as japanese, english, chinese, german, etc. For example, when the user selects english, the language designation reception unit 28 translates the display on the screen into english, and also translates the information in the sample type database 211 into english for use in each of the above-described processes.

Next, an embodiment of an analysis system according to the present invention will be described.

The analysis system 100 of the present embodiment is used for measuring the contents of the above-mentioned six harmful substances contained in the target sample, and in the case where the harmful substances are contained, compares the contents with a threshold value defined in the restriction of elimination of the RoHS rule to determine whether or not the target sample is suitable, in addition to the use of the sample type determination device of the above-mentioned embodiment. The contents of lead, mercury, cadmium and hexavalent chromium in the six harmful substances were measured by an X-ray fluorescence analyzer (EDX), and the contents of PBB (polybrominated diphenyl oxide) and PBDE (polybrominated diphenyl ether) were measured by a gas chromatography-mass spectrometer (Py-GCMS) equipped with a thermal decomposition device (pyrolyzer). In addition, Inductively Coupled Plasma (ICP) emission spectroscopy, ultraviolet-visible spectrophotometer (UV), gas chromatography-mass spectrometry (GCMS), and the like are used for precise quantitative analysis.

As shown in fig. 7, the analysis system of the present embodiment is roughly composed of an analysis device group 110(EDX 111, Py-GCMS 112, ICP 113, UV 114, and the like) and a control/data processing unit 120. The data acquired by the group of analysis devices 110 is sequentially stored in the storage unit 121 of the control/data processing unit 120.

The control/data processing unit 120 includes, as functional blocks, a reference information input receiving unit 122, a morpheme analyzing unit 123, a target sample information input receiving unit 124, a database storage unit 125, a category candidate extracting unit 126, a category candidate presenting unit 127, a language designation receiving unit 128, a measurement executing unit 130, a measurement data reading unit 131, a determining unit 132, and a report creating unit 133 in addition to the storage unit 121. Further, functional blocks having the same functions as those of the sample type identification device shown in fig. 1 are denoted by the same reference numerals as those in fig. 1 in the last two digits, and descriptions thereof are omitted as appropriate. The entity of the control/data processing section 120 is a personal computer, and these functional blocks are specifically realized by executing an analysis system program installed in the computer. Further, an input unit 140 and a display unit 150 are connected to the control/data processing unit 120.

The storage unit 121 stores a determination criterion database 1212 in addition to the sample type database 1211 similar to the above-described embodiment. A determination criterion database 1212 is stored for each analysis device. For example, the database shown in fig. 8 is stored as the determination criterion database 1212 for EDX 111.

As described above, EDX 111 is capable of measuring the content of Cd, Pb, Cr, Hg, Br. Therefore, threshold values corresponding to the respective elements are stored, so that the screening analysis of the sample can be easily performed by performing the measurement using EDX 111. These thresholds are set according to the material (base material) of each sample. This is because the detection sensitivity differs depending on the type of the material (base material) of the sample, the detection sensitivity increases in the order of resin, Al, Fe, Cu, and Sn, and a calibration curve corresponding to each detection sensitivity is used. The reason why the threshold values have ranges is that the measurement error is set to ± 30%.

The operation of the analysis system according to the present embodiment will be described below by taking, as an example, a case where lead in a target sample is quantitatively measured using EDX 111 and a case where whether the target sample is acceptable or not is determined based on quantitative lead data obtained by the measurement using EDX 111.

When the user causes the analysis system program to run, an initial screen shown in fig. 9 is displayed. Five buttons of "sample type confirmation", "determination reference input", "measurement execution", "measurement data determination", and "language change" are displayed on the initial screen. Here, since the operation when the buttons other than the "measurement execution" and the "measurement data determination" are pressed is the same as in the above-described embodiment, only the operation when the "measurement execution" and the "measurement data determination" buttons are pressed will be described.

In the initial screen of fig. 9, when the user presses the "measurement execution" button, the measurement execution unit 130 causes the user to select an analysis device, and then prompts the input of measurement conditions and the setting of a sample to the selected analysis device, when the start of measurement is instructed by a predetermined operation via the input unit 140 after the user has performed these operations, the measurement of a target sample and the quantification of an element to be analyzed are performed, the operation related to the measurement and quantification is the same as in the conventional art, and therefore, the description of the measurement and quantification is omitted here.

When the user presses a "measurement data determination" button on the initial screen, the measurement data reading unit 131 causes the user to designate a storage location of the measurement data file. When the user designates a measurement data file, the measurement data reading unit 131 checks whether or not the measurement data file contains target sample information, which is language information including a word for giving a feature to a target sample. When these pieces of information are not included, the target sample information input receiving unit 124 is operated to display a field for inputting the target sample information on the screen. In the case where the target sample information has been input by the user and has been saved together with the measurement data when the measurement or the like is performed, this step is omitted.

When the user inputs target sample information (or when the target sample information is already input), the measurement data reading unit 131 reads target sample information and measurement data specified by the user. In the present embodiment, the measurement data is only a quantitative value of lead, but when the measurement data including quantitative values of a plurality of elements is read, the user is caused to specify the measurement data (in this case, the type of the element) to be determined. Next, the category candidate extraction unit 126 compares the target sample information with the keyword groups of each category included in the sample category database 1211. Next, the category candidate presentation unit 127 displays a predetermined number of categories on the display unit 150 (fig. 5) according to the matching degrees.

Conventionally, the following processes have been performed in a screening assay using EDX 111: the measurement result of each target element contained in the target sample is compared with a threshold value prepared in advance, and if the comparison result is smaller than the lower limit value, the determination is qualified, if the comparison result is larger than the upper limit value, the determination is unqualified, and if the comparison result is a value in the range of the threshold value, the high-precision measurement is promoted by using other devices. Since the threshold value used in this case is always the same regardless of the characteristics of the target sample, it is necessary to check whether or not the target sample is a predetermined object to be excluded by the RoHS directive every time, which is troublesome. In addition, in the case of a user who is not familiar with the RoHS command, the target sample that is the target object for exclusion of the RoHS command may be overlooked, and the target sample may be erroneously determined to be a non-specification object even if the target sample satisfies the requirement for exclusion.

In the analysis system according to the present embodiment, the user is caused to input information (target sample information) including a word or phrase for giving a feature to the target sample, the degree of matching between the information and the keyword group of each category in the sample category database 1211 is obtained, and the category candidate corresponding to the target sample is displayed on the display unit 150 based on the degree of matching. Therefore, the user can easily determine whether or not the target sample belongs to the category specified in the restriction rule for the RoHS directive by simply checking the category candidates shown in the display unit 150.

For ease of explanation, the following description will be given taking as an example a case where the user inputs "galvanized steel sheet" as target sample information and there is only one category candidate that matches the word (fig. 10). The same applies to the case where a plurality of category candidates exist and are displayed.

When the user confirms the category candidates displayed on the display unit 150, determines that the target sample belongs to a category specified in the restriction rules of the RoHS directive, and presses the "category determination" button, the determination unit 132 extracts a word (3500ppm) composed of a combination of a numerical value and a unit of a predetermined physical quantity (in this example, ppm) from the words of the determination criteria of each category candidate, compares the word with the quantitative value (2000ppm) obtained by the measurement as a determination threshold, and displays the determination result (OK) of the target sample acceptance or rejection (fig. 11). When a plurality of category candidates exist, the quantitative value is compared with a determination threshold value for each category candidate, and the determination result is displayed. On the other hand, when the user determines that the target sample does not belong to the category specified in the restriction rules for RoHS command and presses the "normal determination" button, the determination unit 132 compares the normal determination threshold value described with reference to fig. 8 with the fixed amount value, and displays the result of determination as to whether the target sample is acceptable or not. The unit of the physical quantity may be determined in advance as described above, or may be input by the user at the time of inputting the target sample information.

When the determination unit 132 completes the determination of the acceptance or rejection of the target sample, the report creation unit 133 creates a report in which the sample name, the target sample information, and the acceptance or rejection determination result input by the user are described in a predetermined format, displays the report on the display unit 150, and stores the report in the storage unit 121. As the predetermined format, for example, a format submitted to manufacturer obligations of electric and electronic devices exported from the european union for proving that the devices satisfy the requirements of the RoHS directive can be used.

Next, an embodiment of the analysis network system according to the present invention will be described.

As shown in fig. 12, the analysis network system 200 includes a cloud server 220 and a plurality of analysis systems 240 (only one of which is shown in fig. 12) connectable to the cloud server 220 via a network. The analysis system is installed in an analysis center or the like using a plurality of countries having different languages. In addition to the cloud server 220 accessible from the analysis system 240 via the network, the cloud server 220 can also be accessed from analysis/browsing computers 260 (only one is shown in fig. 12) via the network.

The cloud server 220 includes, as functional blocks, a reference information input receiving unit 222, a morphological analysis unit 223, a target sample information input receiving unit 224, a database storage unit 225, a category candidate extraction unit 226, a category candidate presentation unit 227, a language designation receiving unit 228, a measurement data reading unit 231, a determination unit 232, and a report creation unit 233 in addition to the storage unit 221 in which the sample type database 2211 and the determination reference database 2212 are stored. That is, the control/data processing unit 120 of the analysis system 100 according to the embodiment includes the respective components (the storage unit and the respective functional blocks) other than the measurement unit.

Meanwhile, the analysis system 240 includes an analysis device 250 and a control/data processing unit 241 connected to the analysis device 250, and the control/data processing unit 241 includes a measurement execution unit 2412 as a functional block in addition to the storage unit 2411.

In the analysis network system 200, when a user instructs to measure a target sample, the measurement execution unit 2412 of the analysis system 240 controls the analysis device 250 to acquire measurement data. In the present embodiment, the user is caused to input target sample information including the name of a target sample and a keyword or the like for giving a feature to the sample before the measurement is started. The measurement data acquired by the analyzer 250 is sequentially stored in the storage unit 2411 of the control/data processing unit 241 together with the name of the target sample and the target sample information. The control/data processing unit 241 transfers the measurement data and the like stored in the storage unit 2411 to the cloud server 220 at a predetermined cycle (for example, every day). The cloud server 220 stores measurement data and the like received from each of the plurality of analysis systems 240 in the storage unit 221 together with an identification number (ID) of the analysis system.

When the cloud server 220 is accessed from the analysis system 240 or the analysis/browsing computer 260, a button other than the "measurement execution" button in the screen shown in fig. 9 is displayed. The operation when each button is operated is the same as that in the analysis system described above, and therefore, a detailed description thereof is omitted, but the operation is different from that in the above embodiment in that each operation is performed by a function block of the cloud server 220.

As in the above-described embodiment, the analysis network system can be switched to a desired language by pressing the "language change" button. Thus, it is possible to handle various requests from analysis systems provided at analysis centers and the like in a plurality of countries that differ in the language used in one cloud server 220. Further, even when the determination criteria are input in different languages from the plurality of analysis systems 240 and the sample type database 2211 is created, the language designation receiving unit translates the data into a language desired by the user, and therefore analysis of the measurement data and the like can be performed without any problem. Further, the determination criteria and measurement data input from the plurality of analysis systems can be stored in the storage unit 221 of the cloud server 220, and can be accessed from any analysis system or analysis/browsing computer. Therefore, for example, the following operations can be performed: the analysis/browsing computer 260 at one analysis site reads the measurement data acquired by the analysis center in each country stored in the storage unit 221 of the cloud server 220, determines whether each target sample is acceptable, and creates a report on each target sample.

The above embodiments are examples, and can be modified as appropriate in accordance with the spirit of the present invention. In the above embodiments, the Restriction of elimination of the RoHS instruction was described as an example, but various standards such as elv (end of life vehicles) instruction, REACH (Registration, Evaluation, Authorization and recovery of logicals), and the like can be used in the same manner. In addition, the same configuration can be used not only for determining the content of the harmful substance but also for confirming a reference corresponding to a product from among a plurality of references specified for each product type when, for example, in order to confirm that the product manufactured in a factory or the like is a non-defective product satisfying a predetermined reference, whether the product is non-defective or not is determined by comparing measurement data obtained by sampling and analyzing a part of the product with the predetermined reference.

In the sample type determination device according to the above-described embodiment, the description has been given by taking as an example the case of using a sample type database in which the type of a sample, the term of the determination criterion, and the keyword group extracted from the term are associated with each other.

In the analysis system according to the above embodiment, the case where the target sample is measured using EDX 111 as the analysis device has been described as an example, but the same configuration as described above can be adopted also in the case where the target sample is measured using another analysis device and in the case where the presence or absence of the target sample is determined based on the measurement data. In the analysis system according to the above embodiment, the determination unit extracts the threshold value from the word of the determination criterion every time, but the threshold value may be associated with the sample type or the like in advance in the sample type database, for example.

In addition, the analysis network system 200 according to the modification described above employs the following configuration: the cloud server 220 is provided with a plurality of functional blocks, and the control/data processing unit 241 of the analysis system 240 is provided with only the measurement execution unit 2412 as a functional block, but may be configured as follows: the control/data processing unit 241 of the analysis system 240 includes a part or all of the functional blocks such as the category candidate extraction unit 226, the category candidate presentation unit 227, the language designation reception unit 228, the measurement data reading unit 231, the determination unit 232, and the report creation unit 233. Alternatively, both the cloud server 220 and the control/data processing unit 241 of the analysis system 240 may have the above-described functional blocks. The analysis network system 200 can also be configured without using the cloud server 220 by providing the data processing unit 241 or the analysis/browsing computer 260 of any of the analysis systems 240 with the functions of the cloud server 220 of the above-described embodiments.

Description of the reference numerals

20: a data processing unit; 21: a storage unit; 211: a sample class database; 22: a reference information input receiving unit; 23: a morpheme analyzing unit; 24: a target sample information input receiving unit; 25: a database storage unit; 26: a category candidate extraction unit; 27: a category candidate presenting unit; 28: a language designation receiving section; 100: an analysis system; 110: a group of analysis devices; 120: a control/data processing section; 121: a storage unit; 1211: a sample class database; 1212: a criterion database; 122: a reference information input receiving unit; 123: a morpheme analyzing unit; 124: a target sample information input receiving unit; 125: a database storage unit; 126: a category candidate extraction unit; 127: a category candidate presenting unit; 128: a language designation receiving section; 130: a measurement execution unit; 131: a measurement data reading unit; 132: a determination unit; 133: a report making section; 200: analyzing the network system; 220: a cloud server; 221: a storage unit; 2211: a sample class database; 2212: a criterion database; 222: a reference information input receiving unit; 223: a morpheme analyzing unit; 224: a target sample information input receiving unit; 225: a database storage unit; 226: a category candidate extraction unit; 227: a category candidate presenting unit; 228: a language designation receiving section; 232: a determination unit; 233: a report making section; 240: an analysis system; 241: a control/data processing section; 2411: a storage unit; 2412: a measurement execution unit; 250: an analysis device; 260: a computer for parsing/browsing.

Claims

1. A sample type identification device for identifying a type to which a target sample belongs from among a plurality of types, each of which is defined with a reference, for classifying the sample, the sample type identification device comprising:

2. The apparatus for specifying a sample type according to claim 1, further comprising:

3. The sample class determination apparatus according to claim 2,

4. The sample class determination apparatus according to claim 2,

the morpheme analyzing unit extracts a keyword group from the reference information.

5. The sample class determination apparatus according to claim 4,

the morpheme analyzing unit extracts a word composed of a combination of a numerical value included in the keyword group, a unit of a physical quantity, and a predetermined word indicating a magnitude relation with the numerical value, and creates a numerical expression based on the word,

6. An analysis system comprising, in addition to the respective units provided in the sample type identification device according to claim 1:

h) a measurement data reading unit which receives input of measurement data of a target sample and reads the measurement data; and

i) and a determination unit that extracts, for each of the category candidates extracted by the category candidate extraction unit, a term that is a combination of a numerical value and a unit of a predetermined physical quantity from one or more terms relating to the predetermined criterion as a threshold value, and compares the physical quantity included in the measurement data with the threshold value to determine whether the target sample is acceptable or not.

7. An analysis network system including a base computer and one or more terminal computers connectable to the base computer via a network, the analysis network system comprising:

a) a storage unit provided in the base computer and storing a database in which one or more words relating to a criterion predetermined for each of a plurality of categories are associated with each of the categories;

b) a target sample information input receiving unit provided in the base computer or/and the terminal computer, for receiving input of target sample information, the target sample information being language information including a word that characterizes a target sample;

c) a category candidate extraction unit provided in the base computer or/and the terminal computer, for comparing a word included in the target sample information with the one or more words corresponding to each of the plurality of categories, and extracting a candidate of a category to which the target sample belongs from the plurality of categories according to a degree of matching therebetween; and

d) and a category candidate presenting unit provided in the base computer or/and the terminal computer, for presenting the extracted category candidates to a user.